Innovation graph approach based identification method of sudden load change of electric system
A load mutation, power system technology, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as inability to identify bad data and load mutation
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specific Embodiment approach 1
[0024] Specific implementation mode one: the following combination Figure 1 to Figure 6 Describe this embodiment, the method of this embodiment includes the following steps:
[0025] Step 1, performing topology analysis on a power network with n nodes and b branches, obtaining a spanning tree of the network topology, and then dividing the b branches in the power network into tree branches and connecting branches;
[0026] Step 2. Obtain the innovation value injected into the node in the spanning tree, the active merit innovation value of the tree branch and the active merit innovation value of the connected branch;
[0027] Step 3. After obtaining the innovation value of the connected branch, recalculate the innovation value of the tree branch in each loop in the network, that is, obtain the calculated innovation vector of the connected branch;
[0028] Step 4. Use the branch active innovation vector obtained in step 2 and the calculated innovation vectors of all branches ob...
specific Embodiment approach 2
[0094] Specific embodiment two, this embodiment provides a specific example, see Figure 7 IEEE-30 node system shown, illustrating the ability of the innovation graph to identify sudden load changes. Assume that node 10 has a sudden load increase of 1.74p.u, which is borne by the generators at nodes 2, 5, 8, and 11: the active power output of the generator at node 2 increases by 0.24p.u, and the power generation at nodes 5, 8, and 11 The increase of machine active power output is 0.5p.u. The following describes the identification process of sudden load changes in the two cases of no bad data and bad data.
[0095] Identification of load breaks when there are no bad data:
[0096] In the absence of bad data and topological errors, the calculation results are shown in Table 1. The table lists the measured values, forecast values, innovation values, as well as extrapolation information and innovation difference values. Examining the innovation value difference in the sixth co...
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